2025 / Conference paper
Financial Fraud Detection Using Rich Mobile Money Transaction Datasets
Towards new e-Infrastructure and e-Services for Developing Countries (AFRICOMM 2023), Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol. 588, pp. 190–208. Springer.
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The study uses MoMTSim to simulate mobile money transactions and fraudulent situations, then evaluates six classifiers using precision, recall, F1-score, AUC-ROC, and Matthews correlation coefficient. It compares detection quality with computational demands to inform model selection for mobile money platforms.